PlantGuard: intelligent plant disease detection

PlantGuard: intelligent plant disease detection

This project report is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2024.

Bibliografiske detaljer
Hovedforfatter:	Khanom, Nazifa
Andre forfattere:	Hossain, Muhammad Iqbal
Format:	Project report
Sprog:	English
Udgivet:	Brac University 2024
Fag:	Leaf textures Texture features CNN Convolutional neural network Image data analysis Deep learning Disease detection Plant diseases > Diagnosis. Neural networks (Computer science) > Agricultural aspects. Artificial intelligence > Applications in agriculture.
Online adgang:	http://hdl.handle.net/10361/24033

Lignende værker

Plant leaf disease identification
af: Hasan Mahin, Mohammad Rakibul, et al.
Udgivet: (2024)

Detection and classification of Mango Leaf diseases utilizing convolutional neural network models
af: Ferdous, Md.Rubaiat, et al.
Udgivet: (2024)

Deep learning based early Glaucoma detection
af: Islam, Aabrar, et al.
Udgivet: (2024)

Leveraging deep learning algorithms for the timely detection of diseases in bean leaves
af: Fiona, Driciru, et al.
Udgivet: (2024)

Efficient image processing and machine learning approach for predicting retinal diseases
af: Hasib, Mehadi Hasan, et al.
Udgivet: (2021)

Tomato leaf disease detection using convolutional neural network
af: Hasan, Md. Riazul, et al.
Udgivet: (2023)

Pneumonia Disease detection using the convolutional neural network
af: Ashrafee, Md. Iftid, et al.
Udgivet: (2024)

Early detection of parkinson’s disease using image processing and artificial neural network
af: Rumman, Mosarrat, et al.
Udgivet: (2018)

Disease detection system of mango leaves
af: Islam, Sabrina, et al.
Udgivet: (2024)

Plant disease detection using convolutional neural network
af: Hossain, Mohammad Shifat, et al.
Udgivet: (2021)

Design and evaluation of convolutional neural network for detection of Alzheimer’s disease using MRI data
af: Mahbub, Riasat, et al.
Udgivet: (2022)

Automated system for detecting jute plant disease using image processing and machine learning integrated with mobile application
af: Joyee, Faiza Nuzhat, et al.
Udgivet: (2016)

Smart detection and classification of fungal disease in rice plants using image processing techniques
af: Rashed, Akib, et al.
Udgivet: (2024)

Incorporating deep features extracted from convolutional neural networks to utilize machine learning classifiers for improved identification of Maize Leaf Disease
af: Khan, Shama, et al.
Udgivet: (2024)

Autonomous fault diagnosis of commercially available PV modules using high-end deep learning frameworks
af: Tasawar, Ihtyaz Kader, et al.
Udgivet: (2021)

Automated detection of Malignant Lesions in the ovary using deep learning models and XAI
af: Ifty, Md. Hasin Sarwar, et al.
Udgivet: (2024)

A PSO-ANLBF based automated feature extraction method
af: Shakhawat, Sabrina, et al.
Udgivet: (2018)

Classification of Bangladeshi soil texture using convolutional neural network
af: Raj, Hafiz Mohiuddin, et al.
Udgivet: (2023)

An eﬃcient deep learning approach for detecting lung disease from chest X-ray images using transfer learning and ensemble modeling
af: Sagor, Mostofa Kamal, et al.
Udgivet: (2021)

Deep learning-based hybrid multi-task model for adrenocortical carcinoma segmentation and classification
af: Datta, Nirjhor, et al.
Udgivet: (2024)

Comparison of deep transfer learning models for cancer diagnosis
af: Joya, Nadia Islam, et al.
Udgivet: (2023)

Exploring machine learning techniques for symptom-based detection of livestock diseases
af: Niloy, Mahir Ahmed, et al.
Udgivet: (2024)

Traumatic meningeal enhancement detection by deep learning-based biomedical image analysis and handcrafted features extraction
af: Uddin, Mohammad Sakib, et al.
Udgivet: (2024)

Exploring Alzheimer's disease prediction with XAI in various neural network models
af: Rahman, Quazi Ashikur, et al.
Udgivet: (2022)

Enhanced medical image analysis: leveraging CUDA for fast and accurate Pneumonia detection with optimized CNNs
af: Alvi, Md.Waseq Alauddin
Udgivet: (2024)

An efficient deep learning approach for detecting Alzheimer’s disease using brain images
af: Sani, Mehedi Hasan, et al.
Udgivet: (2022)

Explainable AI (XAI) driven skin cancer detection using transformer and CNN based architecture
af: Radiah, Faiza, et al.
Udgivet: (2024)

Clustering and detection of good and bad rail line anchors from images
af: Islam, Samiul, et al.
Udgivet: (2017)

An efficient deep learning approach to detect skin Cancer
af: Islam, Ashfaqul, et al.
Udgivet: (2022)

Explainable Deepfake video detection using Convolutional Neural Network and CapsuleNet
af: Ishrak, Gazi Hasin, et al.
Udgivet: (2022)

Deep Learning based Medicinal Plants Leaf Recognition
af: Mahalanabish, Tonusri
Udgivet: (2023)

An interpretable diagnosis of retinal diseases using vision transformer and Grad-CAM
af: Bhuiyan, Mahdi Hasan, et al.
Udgivet: (2024)

Silent voice: harnessing deep learning for lip-reading in Bangla
af: Shaheen, Munia, et al.
Udgivet: (2024)

Skin cancer classification for seven types of skin lesions
af: Rahman, Md. Tawsifur, et al.
Udgivet: (2024)

Leaf classification by feature extraction using CNN
af: Bhuiyan, Md. Mazharul Islam, et al.
Udgivet: (2020)

Smart agriculture management system for rice disease detection and fertilizer
af: Faiyaz, Md Abrar Hossen, et al.
Udgivet: (2024)

Detecting Deepfake images using deep convolutional neural network
af: Dhar, Arpita, et al.
Udgivet: (2022)

Brain tumor detection with convolutional neural network
af: Galib, Abrar Tahmid, et al.
Udgivet: (2024)

An efficient deep learning approach for brain tumor detection using 3D convolutional neural network
af: Ali, Syed Muaz
Udgivet: (2023)

An efficient deep learning approach to detect neurodegenerative diseases using retinal images
af: Irfanuddin, Chowdhury Mohammad, et al.
Udgivet: (2023)